Detecting molecules in Ariel low resolution transmission spectra
Detecting molecules in Ariel low resolution transmission spectra
复制标题
检测 Ariel 低分辨率透射光谱中的分子
DOI：
10.1007/s10686-023-09911-x
复制
发表时间：
2023
影响因子：
3
通讯作者：
Bocchieri A
中科院分区：
文献类型：
--
作者：
Bocchieri A
ArielSpace使命的目标是在0.5至7.8微米的宽波长范围内观察系外行星大气的各种样本。观测分为四个层次，第一层次是侦察调查。该层旨在在低光谱分辨率下实现足够的信噪比（S/N），以识别无特征光谱或检测关键分子种类，而不必以高置信度限制其丰度。我们引入AP-统计，使用丰度后验从光谱检索推断分子的存在概率在一个给定的行星的大气层中的第1层。我们发现，这种方法预测的概率，以及与输入丰度，检索模型具有可比或更高的复杂性相比，数据时，指示相当大的预测能力。然而，我们也证明了，当检索模型具有较低的复杂性时，P-统计量失去了代表性，表示为包含少于预期的分子。theP-统计的可靠性和预测能力进行评估的H-He为主的大气层的系外行星的模拟人口，预测偏差进行了研究，发现不会对调查的分类产生不利影响。
TheArielSpace Mission aims to observe a diverse sample of exoplanet atmospheres across a wide wavelength range of 0.5 to 7.8 microns. The observations are organized into four Tiers, withTier 1being a reconnaissance survey. This Tier is designed to achieve a sufficient signal-to-noise ratio (S/N) at low spectral resolution in order to identify featureless spectra or detect key molecular species without necessarily constraining their abundances with high confidence. We introduce aP-statistic that uses the abundance posteriors from a spectral retrieval to infer the probability of a molecule’s presence in a given planet’s atmosphere in Tier 1. We find that this method predicts probabilities that correlate well with the input abundances, indicating considerable predictive power when retrieval models have comparable or higher complexity compared to the data. However, we also demonstrate that theP-statistic loses representativity when the retrieval model has lower complexity, expressed as the inclusion of fewer than the expected molecules. The reliability and predictive power of theP-statistic are assessed on a simulated population of exoplanets with H-He dominated atmospheres, and forecasting biases are studied and found not to adversely affect the classification of the survey.